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Age‐related gut bacterial changes during infancy have been widely studied, but it remains still unknown how these changes are associated with immune cell composition. This study's aim was to explore if the temporal development of gut bacteria during infancy prospectively affects immune cell composition. Faecal bacteria and short‐chain fatty acids were analysed from 67 PreventADALL study participants at four timepoints (birth to 12 months) using reduced metagenome sequencing and gas chromatography. Immune cell frequencies were assessed using mass cytometry in whole blood samples at 12 months. The infants clustered into four groups based on immune cell composition: clusters 1 and 2 showed a high relative abundance of naïve cells, cluster 3 exhibited increased abundance of classical‐ and non‐classical monocytes and clusters 3 and 4 had elevated neutrophil levels. At all age groups, we did observe significant associations between the gut microbiota and immune cell clusters; however, these were generally from low abundant species. Only at 6 months of age we observed significant associations between abundant (>8%) species and immune cell clusters. Bifidobacterium adolescentis and Porphyromonadaceae are associated with cluster 1, while Bacteroides fragilis and Bifidobacterium longum are associated with clusters 3 and 4 respectively. These species have been linked to T‐cell polarization and maturation. No significant correlations were found between short‐chain fatty acids and immune cell composition. Our findings suggest that abundant gut bacteria at 6 months may influence immune cell frequencies at 12 months, highlighting the potential role of gut microbiota in shaping later immune cell composition. Our manuscript's main contribution to the field is the novel finding of associations between gut bacteria at different age categories to immune cell composition at 1 year, which supports the notion that gut microbiota composition affects immune cell development during the first year of life. [ABSTRACT FROM AUTHOR]

The Abi protein family consists of putative membrane-bound metalloproteases. While they are involved in membrane anchoring of proteins in eukaryotes, little is known about their function in prokaryotes. In some known bacteriocin loci, Abi genes have been found downstream of bacteriocin structural genes (e.g., pln locus from Lactobacillus plantarum and sag locus from Streptococcus pyogenes), where they probably are involved in self-immunity. By modifying the profile hidden Markov model used to select Abi proteins in the Pfam protein family database, we show that this family is larger than presently recognized. Using bacteriocin-associated Abi genes as a means to search for novel bacteriocins in sequenced genomes, seven new bacteriocin-like loci were identified in Gram-positive bacteria. One such locus, from Lactobacillus sakei 23K, was selected for further experimental study, and it was confirmed that the bacteriocin-like genes (skkAB) exhibited antimicrobial activity when expressed in a heterologous host and that the associated Abi gene (skkI) conferred immunity against the cognate bacteriocin. Similar investigation of the Abi gene plnI and the Abi-like gene plnL from L. plantarum also confirmed their involvement in immunity to their cognate bacteriocins (PlnEF and PlnJK, respectively). Interestingly, the immunity genes from these three systems conferred a high degree of cross-immunity against each other's bacteriocins, suggesting the recognition of a common receptor. Site-directed mutagenesis demonstrated that the conserved motifs constituting the putative proteolytic active site of the Abi proteins are essential for the immunity function of SkkI, and to our knowledge, this represents a new concept in self-immunity. doi: 10.1128/JB.01553-09

A microarray-based comparative genomic hybridization is used to compare the genomic diversity among Enterococcus faecalis strains and Enterococcus faecalis V583. The results have shown that the genes related to stress tolerance is similar in V583 and Enterococcus faecalis strains, suggesting that Enterococcus faecalis has the ability to resist harsh conditions.

Abstract Background Gene finding is a complicated procedure that encapsulates algorithms for coding sequence modeling, identification of promoter regions, issues concerning overlapping genes and more. In the present study we focus on coding sequence modeling algorithms; that is, algorithms for identification and prediction of the actual coding sequences from genomic DNA. In this respect, we promote a novel multivariate method known as Canonical Powered Partial Least Squares (CPPLS) as an alternative to the commonly used Interpolated Markov model (IMM). Comparisons between the methods were performed on DNA, codon and protein sequences with highly conserved genes taken from several species with different genomic properties. Results The multivariate CPPLS approach classified coding sequence substantially better than the commonly used IMM on the same set of sequences. We also found that the use of CPPLS with codon representation gave significantly better classification results than both IMM with protein (p < 0.001) and with DNA (p < 0.001). Further, although the mean performance was similar, the variation of CPPLS performance on codon representation was significantly smaller than for IMM (p < 0.001). Conclusions The performance of coding sequence modeling can be substantially improved by using an algorithm based on the multivariate CPPLS method applied to codon or DNA frequencies.

Abstract Background We sought to assess whether the concept of relative entropy (information capacity), could aid our understanding of the process of horizontal gene transfer in microbes. We analyzed the differences in information capacity between prokaryotic chromosomes, genomic islands (GI), phages, and plasmids. Relative entropy was estimated using the Kullback-Leibler measure. Results Relative entropy was highest in bacterial chromosomes and had the sequence chromosomes > GI > phage > plasmid. There was an association between relative entropy and AT content in chromosomes, phages, plasmids and GIs with the strongest association being in phages. Relative entropy was also found to be lower in the obligate intracellular Mycobacterium leprae than in the related M. tuberculosis when measured on a shared set of highly conserved genes. Conclusions We argue that relative entropy differences reflect how plasmids, phages and GIs interact with microbial host chromosomes and that all these biological entities are, or have been, subjected to different selective pressures. The rate at which amelioration of horizontally acquired DNA occurs within the chromosome is likely to account for the small differences between chromosomes and stably incorporated GIs compared to the transient or independent replicons such as phages and plasmids.

Abstract Background In genomics, a commonly encountered problem is to extract a subset of variables out of a large set of explanatory variables associated with one or several quantitative or qualitative response variables. An example is to identify associations between codon-usage and phylogeny based definitions of taxonomic groups at different taxonomic levels. Maximum understandability with the smallest number of selected variables, consistency of the selected variables, as well as variation of model performance on test data, are issues to be addressed for such problems. Results We present an algorithm balancing the parsimony and the predictive performance of a model. The algorithm is based on variable selection using reduced-rank Partial Least Squares with a regularized elimination. Allowing a marginal decrease in model performance results in a substantial decrease in the number of selected variables. This significantly improves the understandability of the model. Within the approach we have tested and compared three different criteria commonly used in the Partial Least Square modeling paradigm for variable selection; loading weights, regression coefficients and variable importance on projections. The algorithm is applied to a problem of identifying codon variations discriminating different bacterial taxa, which is of particular interest in classifying metagenomics samples. The results are compared with a classical forward selection algorithm, the much used Lasso algorithm as well as Soft-threshold Partial Least Squares variable selection. Conclusions A regularized elimination algorithm based on Partial Least Squares produces results that increase understandability and consistency and reduces the classification error on test data compared to standard approaches.

Abstract Background Multivariate approaches are important due to their versatility and applications in many fields as it provides decisive advantages over univariate analysis in many ways. Genome wide association studies are rapidly emerging, but approaches in hand pay less attention to multivariate relation between genotype and phenotype. We introduce a methodology based on a BLAST approach for extracting information from genomic sequences and Soft- Thresholding Partial Least Squares (ST-PLS) for mapping genotype-phenotype relations. Results Applying this methodology to an extensive data set for the model yeast Saccharomyces cerevisiae, we found that the relationship between genotype-phenotype involves surprisingly few genes in the sense that an overwhelmingly large fraction of the phenotypic variation can be explained by variation in less than 1% of the full gene reference set containing 5791 genes. These phenotype influencing genes were evolving 20% faster than non-influential genes and were unevenly distributed over cellular functions, with strong enrichments in functions such as cellular respiration and transposition. These genes were also enriched with known paralogs, stop codon variations and copy number variations, suggesting that such molecular adjustments have had a disproportionate influence on Saccharomyces yeasts recent adaptation to environmental changes in its ecological niche. Conclusions BLAST and PLS based multivariate approach derived results that adhere to the known yeast phylogeny and gene ontology and thus verify that the methodology extracts a set of fast evolving genes that capture the phylogeny of the yeast strains. The approach is worth pursuing, and future investigations should be made to improve the computations of genotype signals as well as variable selection procedure within the PLS framework.

Abstract Background Lactobacillus sakei is valuable in the fermentation of meat products and exhibits properties that allow for better preservation of meat and fish. On these substrates, glucose and ribose are the main carbon sources available for growth. We used a whole-genome microarray based on the genome sequence of L. sakei strain 23K to investigate the global transcriptome response of three L. sakei strains when grown on ribose compared with glucose. Results The function of the common regulated genes was mostly related to carbohydrate metabolism and transport. Decreased transcription of genes encoding enzymes involved in glucose metabolism and the L-lactate dehydrogenase was observed, but most of the genes showing differential expression were up-regulated. Especially transcription of genes directly involved in ribose catabolism, the phosphoketolase pathway, and in alternative fates of pyruvate increased. Interestingly, the methylglyoxal synthase gene, which encodes an enzyme unique for L. sakei among lactobacilli, was up-regulated. Ribose catabolism seems closely linked with catabolism of nucleosides. The deoxyribonucleoside synthesis operon transcriptional regulator gene was strongly up-regulated, as well as two gene clusters involved in nucleoside catabolism. One of the clusters included a ribokinase gene. Moreover, hprK encoding the HPr kinase/phosphatase, which plays a major role in the regulation of carbon metabolism and sugar transport, was up-regulated, as were genes encoding the general PTS enzyme I and the mannose-specific enzyme II complex (EIIman). Putative catabolite-responsive element (cre) sites were found in proximity to the promoter of several genes and operons affected by the change of carbon source. This could indicate regulation by a catabolite control protein A (CcpA)-mediated carbon catabolite repression (CCR) mechanism, possibly with the EIIman being indirectly involved. Conclusions Our data shows that the ribose uptake and catabolic machinery in L. sakei is highly regulated at the transcription level. A global regulation mechanism seems to permit a fine tuning of the expression of enzymes that control efficient exploitation of available carbon sources.

Abstract Background Enterococci rank among the leading causes of nosocomial infections. The failure to identify pathogen-specific genes in Enterococcus faecalis has led to a hypothesis where the virulence of different strains may be linked to strain-specific genes, and where the combined endeavor of the different gene-sets result in the ability to cause infection. Population structure studies by multilocus sequence typing have defined distinct clonal complexes (CC) of E. faecalis enriched in hospitalized patients (CC2, CC9, CC28 and CC40). Results In the present study, we have used a comparative genomic approach to investigate gene content in 63 E. faecalis strains, with a special focus on CC2. Statistical analysis using Fisher's exact test revealed 252 significantly enriched genes among CC2-strains. The majority of these genes were located within the previously defined mobile elements phage03 (n = 51), efaB5 (n = 34) and a vanB associated genomic island (n = 55). Moreover, a CC2-enriched genomic islet (EF3217 to -27), encoding a putative phage related element within the V583 genome, was identified. From the draft genomes of CC2-strains HH22 and TX0104, we also identified a CC2-enriched non-V583 locus associated with the E. faecalis pathogenicity island (PAI). Interestingly, surface related structures (including MSCRAMMs, internalin-like and WxL protein-coding genes) implicated in virulence were significantly overrepresented (9.1%; p = 0.036, Fisher's exact test) among the CC2-enriched genes. Conclusion In conclusion, we have identified a set of genes with potential roles in adaptation or persistence in the hospital environment, and that might contribute to the ability of CC2 E. faecalis isolates to cause disease.